Deciding with the eye: How the visually manipulated accessibility of information in memory influences decision behavior

Decision situations are typically characterized by uncertainty: Individuals do not know the values of different options on a criterion dimension. For example, consumers do not know which is the healthiest of several products. To make a decision, individuals can use information about cues that are probabilistically related to the criterion dimension, such as sugar content or the concentration of natural vitamins. In two experiments, we investigated how the accessibility of cue information in memory affects which decision strategy individuals rely on. The accessibility of cue information was manipulated by means of a newly developed paradigm, the spatial-memory-cueing paradigm, which is based on a combination of the looking-at-nothing phenomenon and the spatial-cueing paradigm. The results indicated that people use different decision strategies, depending on the validity of easily accessible information. If the easily accessible information is valid, people stop information search and decide according to a simple take-the-best heuristic. If, however, information that comes to mind easily has a low predictive validity, people are more likely to integrate all available cue information in a compensatory manner.

[1]  D. Spalding The Principles of Psychology , 1873, Nature.

[2]  E. Tulving,et al.  Availability versus accessibility of information in memory for words , 1966 .

[3]  Daniel Kahneman,et al.  Availability: A heuristic for judging frequency and probability , 1973 .

[4]  L. Beach,et al.  A Contingency Model for the Selection of Decision Strategies , 1978 .

[5]  B. Fischhoff,et al.  Judged frequency of lethal events , 1978 .

[6]  M. Posner,et al.  Orienting of Attention* , 1980, The Quarterly journal of experimental psychology.

[7]  M. Posner,et al.  Attention and the detection of signals. , 1980, Journal of experimental psychology.

[8]  Russell H. Fazio,et al.  Priming and Frequency Estimation , 1984 .

[9]  Veronica J. Dark,et al.  Perceptual Fluency and Recognition Judgments , 1985 .

[10]  R. Hastie,et al.  The relationship between memory and judgment depends on whether the judgment task is memory-based or on-line , 1986 .

[11]  G. Logan Toward an instance theory of automatization. , 1988 .

[12]  R. Rescorla Behavioral studies of Pavlovian conditioning. , 1988, Annual review of neuroscience.

[13]  H Pashler,et al.  Cross-dimensional interaction and texture segregation , 1988, Perception & psychophysics.

[14]  Eric J. Johnson,et al.  Adaptive Strategy Selection in Decision Making. , 1988 .

[15]  G. Gigerenzer,et al.  Probabilistic mental models: a Brunswikian theory of confidence. , 1991, Psychological review.

[16]  F. Strack,et al.  Ease of retrieval as information: Another look at the availability heuristic. , 1991 .

[17]  J. Theeuwes Cross-dimensional perceptual selectivity , 1991, Perception & psychophysics.

[18]  Kevin J. Hawley,et al.  Contribution of perceptual fluency to recognition judgments. , 1991, Journal of experimental psychology. Learning, memory, and cognition.

[19]  J. Theeuwes Perceptual selectivity for color and form , 1992, Perception & psychophysics.

[20]  John W. Payne,et al.  The adaptive decision maker: Name index , 1993 .

[21]  Eric J. Johnson,et al.  The adaptive decision maker , 1993 .

[22]  G Gigerenzer,et al.  Reasoning the fast and frugal way: models of bounded rationality. , 1996, Psychological review.

[23]  S. Yantis,et al.  Visual attention: control, representation, and time course. , 1997, Annual review of psychology.

[24]  Frank R. Kardes,et al.  Consumer Behavior and Managerial Decision Making , 1998 .

[25]  Ulrich Hoffrage,et al.  When do people use simple heuristics, and how can we tell? , 1999 .

[26]  N. Schwarz,et al.  Effects of Perceptual Fluency on Judgments of Truth , 1999, Consciousness and Cognition.

[27]  P. Todd,et al.  Simple Heuristics That Make Us Smart , 1999 .

[28]  Gerd Gigerenzer,et al.  Fast and frugal heuristics: The adaptive toolbox. , 1999 .

[29]  A. Bröder Assessing the empirical validity of the "take-the-best" heuristic as a model of human probabilistic inference. , 2000, Journal of experimental psychology. Learning, memory, and cognition.

[30]  Wasserman,et al.  Bayesian Model Selection and Model Averaging. , 2000, Journal of mathematical psychology.

[31]  Iver Mysterud,et al.  Take the best , 2000 .

[32]  C. Koch,et al.  A saliency-based search mechanism for overt and covert shifts of visual attention , 2000, Vision Research.

[33]  Daniel C. Richardson,et al.  Representation, space and Hollywood Squares: looking at things that aren't there anymore , 2000, Cognition.

[34]  C. Koch,et al.  Computational modelling of visual attention , 2001, Nature Reviews Neuroscience.

[35]  G Douglas Olsen,et al.  Salient stimuli in advertising: the effect of contrast interval length and type on recall. , 2002, Journal of experimental psychology. Applied.

[36]  Eric J. Johnson,et al.  When Web Pages Influence Choice: Effects of Visual Primes on Experts and Novices , 2002 .

[37]  Pierre Chandon,et al.  When Are Stockpiled Products Consumed Faster? A Convenience–Salience Framework of Postpurchase Consumption Incidence and Quantity , 2002 .

[38]  Derrick J. Parkhurst,et al.  Modeling the role of salience in the allocation of overt visual attention , 2002, Vision Research.

[39]  A. Bröder Decision making with the "adaptive toolbox": influence of environmental structure, intelligence, and working memory load. , 2003, Journal of experimental psychology. Learning, memory, and cognition.

[40]  C. Gettys,et al.  Emerging Perspectives on Judgment and Decision Research: Memory as a Fundamental Heuristic for Decision Making , 2003 .

[41]  B. Newell,et al.  Take the best or look at the rest? Factors influencing "one-reason" decision making. , 2003, Journal of experimental psychology. Learning, memory, and cognition.

[42]  B. Newell,et al.  Empirical tests of a fast-and-frugal heuristic: Not everyone "takes-the-best" , 2003 .

[43]  A. Bröder,et al.  Take the best versus simultaneous feature matching: probabilistic inferences from memory and effects of representation format. , 2003, Journal of experimental psychology. General.

[44]  M. Lee,et al.  Evidence accumulation in decision making: Unifying the “take the best” and the “rational” models , 2004, Psychonomic bulletin & review.

[45]  L. Jacoby,et al.  Becoming Famous Overnight : Limits on the Ability to Avoid Unconscious Influences of the Past , 2004 .

[46]  Derrick J. Parkhurst,et al.  Texture contrast attracts overt visual attention in natural scenes , 2004, The European journal of neuroscience.

[47]  G. Altmann Language-mediated eye movements in the absence of a visual world: the ‘blank screen paradigm’ , 2004, Cognition.

[48]  Christian Unkelbach,et al.  The Learned Interpretation of Cognitive Fluency , 2006, Psychological science.

[49]  A. Bröder,et al.  Adaptive flexibility and maladaptive routines in selecting fast and frugal decision strategies. , 2006, Journal of experimental psychology. Learning, memory, and cognition.

[50]  Arndt Bröder,et al.  Stimulus format and working memory in fast and frugal strategy selection , 2006 .

[51]  J. Rieskamp,et al.  SSL: a theory of how people learn to select strategies. , 2006, Journal of experimental psychology. General.

[52]  Daniel M. Oppenheimer,et al.  Easy does it: The role of fluency in cue weighting , 2007 .

[53]  W. Gaissmaier The mnemonic decision maker: how search in memory shapes decision making , 2007 .

[54]  Stefan M. Herzog,et al.  Fluency heuristic: a model of how the mind exploits a by-product of information retrieval. , 2008, Journal of experimental psychology. Learning, memory, and cognition.

[55]  J. Henderson,et al.  Taking a new look at looking at nothing , 2008, Trends in Cognitive Sciences.

[56]  Ulrich Hoffrage,et al.  Inferences under time pressure: how opportunity costs affect strategy selection. , 2008, Acta psychologica.

[57]  Daniel M. Oppenheimer The secret life of fluency , 2008, Trends in Cognitive Sciences.

[58]  Michael S. Fine,et al.  Visual Salience Affects Performance in a Working Memory Task , 2009, The Journal of Neuroscience.

[59]  Andreas Glöckner,et al.  Foundations for tracing intuition: Challenges and methods , 2010 .

[60]  Andreas Glöckner,et al.  Outcome-based strategy classification , 2010 .

[61]  Julian N. Marewski,et al.  Cognitive niches: an ecological model of strategy selection. , 2011, Psychological review.

[62]  B. Hilbig,et al.  Methodological notes on model comparisons and strategy classification: A falsificationist proposition , 2011, Judgment and Decision Making.

[63]  Frank Renkewitz,et al.  Memory indexing: a novel method for tracing memory processes in complex cognitive tasks. , 2012, Journal of experimental psychology. Learning, memory, and cognition.

[64]  Thorsten Pachur,et al.  How do people judge risks: availability heuristic, affect heuristic, or both? , 2012, Journal of experimental psychology. Applied.

[65]  Arndt Bröder,et al.  Most people do not ignore salient invalid cues in memory-based decisions , 2012, Psychonomic bulletin & review.

[66]  Eye movements to “nothing” have an active role during visuospatial memory retrieval , 2013 .